The manufacturing of semiconductor wafer and integrated circuits has traditionally employed several types of systems and tools to provide quality control and process monitoring.
For example, wafer geometry systems, ranging from the tabletop gauges to high volume multi-functional sorting systems on state of the art robotic transfer platforms, are used to obtain wafer characterization data to provide an accurate knowledge of wafer dimensional characteristics such as flatness, diameter, thickness, bow, warp, shape, nanotopography, resistivity, backgrind characteristics, thermal shape change, among others. In addition, surface inspection systems are used to identify defects occurring on a surface of a semiconductor wafer, such as particles, scratches, COP's, mounds, dimples, stacking faults, haze and more. Further, certain defect and dimensional analysis systems perform thin film analysis, providing full wafer mapping of surfaces with thin epitaxial film or other dielectric films such as SiO2, CVD, SOI, and photoresist with transition region thickness and substrate carriers.
Software has been developed to analyze the measurement data generated by such systems and transform the data to produce information about process-induced defects, system degradation, and other potential problem areas. Thus, data from dimensional and inspection systems allow process engineers to maintain process control and optimal tool parameters, and provide them with valuable insight when developing new advanced wafer processes.
However, with the wide variety of and large amounts of data from the numerous tools used in the manufacturing of semiconductor wafer and integrated circuits, managing, analyzing and automating wafer data has become extremely complicated. Traditionally, the data generated by the dimensional and inspection systems were treated separately, not combined. In the past, wafer data management and analysis systems have been developed for dimensional systems, but they have not included data from surface inspection systems such as defect evaluation systems. Defect evaluation systems were developed, but they did not support wafer characterization tools or automation features. Because the disparities between the data from the numerous systems, the ability of engineering to use all of the data available to it to optimize manufacturing processes was limited.
In addition, given the large amounts of data developed by each of the numerous tools, it has become apparent that traditional methods of managing older data are inadequate. Analyzing and automating wafer data has become extremely complicated. Further, cross-site transfer of data and review of data from multiple fabrication processes in order to control production across several manufacturing processes, while theoretically possible, was rendered practically difficult by the sheer amount of data and wide variation in types of data to be transferred and reviewed. It would be desirable to provide for transfer of only selective data to a central system to provide multi-plant production management.
Further, the amount of data produced during such production is so great that purging data after a selected interval is necessary in order to make storage room available for new data to be produced. However, some data in a data set could be useful for longer than other data. Traditionally, data purging is conducted by establishing a threshold data and deleting data older than that date. Therefore, it has been necessary to store un-needed data for longer than it was necessary, simply because it was in the same data set as the needed data. It would be desirable to provide a purging system in which data in a data set may be purged as it is no longer needed.
It has become desirable to provide a system for integrated wafer data management and process monitoring system for data management, analysis, and automation from all systems used in the wafer and integrated circuit production process, including both dimensional and inspection systems, along with the software for analyzing such data.